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Updated: Jan 2, 2026

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
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Proposal for an Embedded System Architecture Using a GNDVI Algorithm to Support UAV-Based Agrochemical Spraying.

Maik Basso1, Diego Stocchero2, Renato Ventura Bayan Henriques1

  • 1Electrical Engineering Graduate Program, Federal University of Rio Grande do Sul (UFRGS), 90035-007 Porto Alegre, Brazil.

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Summary

Precision agriculture uses unmanned aerial vehicles (UAVs) for targeted chemical application. An onboard image processing system with a Normalized Difference Vegetation Index (NDVI) algorithm enables efficient, low-cost spraying, reducing chemical use and residues.

Keywords:
NDVI algorithmUAV automated systemsembedded image processing systemsprecision agriculture applications

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Area of Science:

  • Precision Agriculture
  • Agricultural Engineering
  • Robotics

Background:

  • Efficient chemical application in agriculture is crucial for cost reduction and minimizing residues.
  • Unmanned Aerial Vehicles (UAVs) offer a cost-effective alternative to manned aircraft for targeted spraying.
  • UAVs enable fine-grained application, unlike conventional mass spraying methods.

Purpose of the Study:

  • To design an embedded real-time UAV spraying control system.
  • To integrate onboard image processing for precise chemical application.
  • To utilize the Normalized Difference Vegetation Index (NDVI) for detecting chemical needs.

Main Methods:

  • Developed an efficient NDVI algorithm for low-cost embedded hardware (Raspberry Pi 3).
  • Integrated the algorithm into a UAV for real-time spraying control and image processing.
  • Conducted laboratory and field tests for system validation under real-world conditions.

Main Results:

  • The system demonstrated efficient processing and low energy consumption on embedded hardware.
  • CPU usage was approximately 20% (HD images) and 4% (low-res images).
  • Memory consumption was around 70 MB (HD images) and 20.3 MB (low-res images), with an average current of 0.11 A.

Conclusions:

  • The proposed UAV spraying system is efficient for embedded applications.
  • The system provides accurate measurements comparable to commercial equipment.
  • This technology supports reduced chemical usage and improved agricultural practices.